# Ulta Scraper (`mscraper/ulta-scraper`) Actor The Ulta Scraper is a powerful tool built to scrape detailed product data from the Ulta. It can retrieve important product data such as product name, skuId, brand, rating, reviews, list price, and more. - **URL**: https://apify.com/mscraper/ulta-scraper.md - **Developed by:** [mscraper](https://apify.com/mscraper) (community) - **Categories:** E-commerce - **Stats:** 107 total users, 0 monthly users, 100.0% runs succeeded, 3 bookmarks - **User rating**: No ratings yet ## Pricing $30.00/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Ulta scraper ### What does Ulta Scraper do? The Ulta Scraper is a powerful tool built to scrape detailed product data from the [Ulta](https://www.ulta.com/). It can retrieve important product data such as product name, skuId, brand, rating, reviews, list price, and more. ### Why scrape Ulta? Ulta is a well-known American chain of beauty stores. Here are four potential benefits of scraping data from Ulta: ➡️ **Market Research**: By scraping data from Ulta, you can gain valuable insights into market trends, popular products, pricing strategies, and promotional offers. This information can guide business decisions and marketing strategies. ➡️ **Competitor Analysis**: The data from Ulta can provide an understanding of what products are being offered by a major competitor. This can help businesses in the same industry strategize and compete effectively. ➡️ **Price Monitoring**: Ulta's data can be used for price monitoring. This would allow a company to track changes in prices over time, providing insights into sales, discounts, and price fluctuations. ➡️ **Identifying Marketing Trends**: Ulta's promotional texts and sales events can provide insights into current marketing trends in the beauty industry. This data can be used to optimize marketing campaigns. ### How much will it cost to scrape Ulta? Apify gives you $5 free usage credits every month on the [Apify Free plan](https://apify.com/pricing). You can get up to 10,000 results per month from Ulta Scraper for that, so those 10,000 results will be completely free But if you need to get more data regularly from Ulta, you should grab an Apify subscription. We recommend our [$49/month Starter plan](https://apify.com/pricing) - you can get up to 100,000 every month with the $49 monthly plan! Or get 1,000,000 results for $499 with the [Scale plan](https://apify.com/pricing) - wow! ### How to scrape Ulta? It's easy to scrape Ulta with Ulta Scraper. Just follow these few steps and you'll get your data in a few minutes. 1. Click on Try for free. 2. Add URLs in input. 3. Click on Run. 4. When Ulta Scraper has finished, preview or download your data from the Dataset tab. Example of valid URLs: `https://www.ulta.com/shop/hair/shampoo-conditioner/dry-shampoo` `https://www.ulta.com/shop/fragrance/womens-fragrance/perfume?scent=fruity+%26+citrus` ### Results The output from Ulta Scraper is stored in the dataset. After the run is finished, you can download the dataset in various data formats (JSON, CSV, XML, RSS, HTML Table). ```json { "dataCapture": null, "skuId": "2604512", "action": { "label": null, "url": "https://www.ulta.com/p/perfect-hair-day-dry-shampoo-pimprod2037265?sku=2604512", "navigationType": "push" }, "productId": "pimprod2037265", "bookmarked": false, "image": { "imageUrl": "https://media.ulta.com/i/ulta/2604512", "name": "2604512", "isCaptionsEnabled": false, "closedCaptionUrl": null, "videoUrl": null, "videoProfiles": null, "metaData": { "mediaType": "img", "isCaptionsEnabled": false, "imageTemplate": "None", "width": null, "height": null, "aspectRatio": null, "isImage": true } }, "altImage": null, "bookmarkAccessibility": null, "addToBagAccessibility": null, "badge": "", "sponsored": false, "brandName": "Living Proof", "productName": "Perfect Hair Day Dry Shampoo", "priceLabel": "", "rating": 4.6, "reviewCount": 2728, "listPrice": "$30.00 - $43.00", "salePrice": null, "discount": null, "promoText": " Free Gift with Purchase", "additionalOffersText": "+1 offers", "reviewAccessibilityLabel": "4.6 out of 5 stars ; 2728 reviews", "variantLabel": "2 sizes" } ```` ### Is it legal to scrape Ulta? Note that personal data is protected by GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers. We also recommend that you read our blog post: [is web scraping legal?](https://blog.apify.com/is-web-scraping-legal/) ### Contact Please feel free to browse through the diverse array of web scrapers available on [my Apify profile](https://apify.com/mscraper). If a custom solution or extra options are what you're seeking, don't hesitate to get in touch with me directly at . # Actor input Schema ## `startUrls` (type: `array`): URLs to start with. ## `proxy` (type: `object`): Select proxies to be used by your crawler. ## `resultsLimit` (type: `integer`): Maximum number of results ## Actor input object example ```json { "startUrls": [ { "url": "https://www.ulta.com/shop/hair/shampoo-conditioner/dry-shampoo" } ], "proxy": { "useApifyProxy": true, "apifyProxyCountry": "US" }, "resultsLimit": 44 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "startUrls": [ { "url": "https://www.ulta.com/shop/hair/shampoo-conditioner/dry-shampoo" } ], "proxy": { "useApifyProxy": true, "apifyProxyCountry": "US" }, "resultsLimit": 44 }; // Run the Actor and wait for it to finish const run = await client.actor("mscraper/ulta-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "startUrls": [{ "url": "https://www.ulta.com/shop/hair/shampoo-conditioner/dry-shampoo" }], "proxy": { "useApifyProxy": True, "apifyProxyCountry": "US", }, "resultsLimit": 44, } # Run the Actor and wait for it to finish run = client.actor("mscraper/ulta-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "startUrls": [ { "url": "https://www.ulta.com/shop/hair/shampoo-conditioner/dry-shampoo" } ], "proxy": { "useApifyProxy": true, "apifyProxyCountry": "US" }, "resultsLimit": 44 }' | apify call mscraper/ulta-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=mscraper/ulta-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Ulta Scraper", "description": "The Ulta Scraper is a powerful tool built to scrape detailed product data from the Ulta. It can retrieve important product data such as product name, skuId, brand, rating, reviews, list price, and more.", "version": "0.0", "x-build-id": "hTaHkMclQZiKYrjda" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/mscraper~ulta-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-mscraper-ulta-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/mscraper~ulta-scraper/runs": { "post": { "operationId": "runs-sync-mscraper-ulta-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/mscraper~ulta-scraper/run-sync": { "post": { "operationId": "run-sync-mscraper-ulta-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "startUrls": { "title": "Start URLs", "type": "array", "description": "URLs to start with.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "proxy": { "title": "Proxy configuration", "type": "object", "description": "Select proxies to be used by your crawler." }, "resultsLimit": { "title": "Results limit (listing)", "minimum": 44, "type": "integer", "description": "Maximum number of results" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```